DocumentCode :
3601221
Title :
Laplacian Scale-Space Behavior of Planar Curve Corners
Author :
Xiaohong Zhang ; Ying Qu ; Dan Yang ; Hongxing Wang ; Kymer, Jeff
Author_Institution :
Key Lab. of Dependable Service Comput. in Cyber Phys. Soc., Chongqing, China
Volume :
37
Issue :
11
fYear :
2015
Firstpage :
2207
Lastpage :
2217
Abstract :
Scale-space behavior of corners is important for developing an efficient corner detection algorithm. In this paper, we analyze the scale-space behavior with the Laplacian of Gaussian (LoG) operator on a planar curve which constructs Laplacian Scale Space (LSS). The analytical expression of a Laplacian Scale-Space map (LSS map) is obtained, demonstrating the Laplacian Scale-Space behavior of the planar curve corners, based on a newly defined unified corner model. With this formula, some Laplacian Scale-Space behavior is summarized. Although LSS demonstrates some similarities to Curvature Scale Space (CSS), there are still some differences. First, no new extreme points are generated in the LSS. Second, the behavior of different cases of a corner model is consistent and simple. This makes it easy to trace the corner in a scale space. At last, the behavior of LSS is verified in an experiment on a digital curve.
Keywords :
curve fitting; object detection; CSS; LSS map; Laplacian scale-space behavior; Laplacian-of-Gaussian operator; LoG operator; corner detection algorithm; curvature scale space; digital curve; planar curve corners; Analytical models; Cascading style sheets; Detectors; Educational institutions; Laplace equations; Mathematical model; Trajectory; Corner Detection; Corner detection; Laplacian of Gaussian; Planar Curve; Scale Space; planar curve; scale space;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2015.2396074
Filename :
7018927
Link To Document :
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